Lead - Business Analytics

Role: Lead

Required Skills: Data Analytics

Qualification: BACHELOR OF COMPUTER SCIENCE

Experience: 10 - 15 Years

Function: TECHNOLOGY

Apply By: 2026-12-25

Role: Lead - Business Analytics - Commercial, Manufacturing & Supply Chain Analytics

Location: Santa Clara, CA

We are seeking a Business Analytics Lead - Commercial, Manufacturing & Supply Chain Analytics for the newly formed

Data & Analytics unit on the US West Coast. This senior, onsite role leads the commercial, manufacturing and supply

chain Business Analytics with AI/ML capability, combining domain-led consulting with hands-on solution leadership. The

lead will engage customer operations and technology leaders to prioritize high-value AI/ML use cases, architect solutions

and take them from PoC through pilot to production with offshore engineering, data science and CoE teams.

Key Responsibilities

l Lead the commercial, manufacturing and supply chain AI/ML capability for the Data & Analytics unit, combining

domain-led consulting with hands-on solution leadership.

l Engage manufacturing, operations, planning, logistics, procurement and technology leaders to identify problems,

assess data readiness and prioritize high-value AI/ML use cases.

l Facilitate discovery and design workshops, define target architectures and convert opportunities into a practical

roadmap with measurable operational outcomes.

l Architect solutions for predictive maintenance, quality, yield, forecasting, inventory, production planning, logistics and

supply-risk analytics based on customer priorities.

l Guide data preparation, feature engineering, model development, validation, deployment, monitoring and continuous

improvement.

l Ensure solutions integrate securely with enterprise, manufacturing and supply chain platforms and operate reliably

within production workflows.

l Own or contribute to proactive proposals, RFP/RFI responses, estimates, delivery models, demonstrations and

executive presentations.

l Lead PoCs and pilots through production, incorporating MLOps, explainability, responsible AI, monitoring, cost control

and governance.

l Coordinate planning, staffing, technical reviews and execution governance with offshore engineering, data science

and CoE teams.

l Build reusable accelerators, reference architectures and solution assets for manufacturing and supply chain analytics.

l Mentor data scientists, ML engineers and architects, establish technical standards and support opportunity

qualification with account leadership.

Qualifications

Education: Bachelor's degree in Computer Science, Data Science, Industrial Engineering, Operations Research, Supply

Chain, Engineering or a related discipline; Master's or PhD desirable.

Experience: Significant professional experience leading AI/ML and analytics solutions in manufacturing and supply

chain environments, including taking initiatives from use-case discovery through production adoption.

Must-Have Technical / Functional Skills

l Strong AI/ML leadership with hands-on depth in manufacturing and supply chain analytics, from use-case discovery

through production adoption.

l Advanced machine learning and data science using Python, scikit-learn, PyTorch or TensorFlow, including feature

engineering, model selection, evaluation, explainability and optimization.

l Proven delivery of manufacturing use cases such as predictive mainten ance, anomaly detection, quality prediction,

yield improvement, process optimization, computer vision inspection or energy optimization.

l Proven delivery of supply chain use cases such as demand forecasting, inventory optimization, supply risk sensing,

production planning, logistics optimization, order fulfillment or control-tower analytics.

l Experience with time-series forecasting, optimization, simulation and machine learning techniques applied to

operational data.

l Experience integrating enterprise and industrial data from ERP, MES, WMS, TMS, planning platforms, IoT, sensor,

historian and streaming sources.

l Production-scale MLOps: MLflow, model serving and monitoring, feature stores, drift management, CI/CD, Docker

and Kubernetes.

l Expertise in at least one cloud AI and data stack: Google Cloud, Azure or AWS; familiarity with Databricks and/or

Snowflake is desirable.

l Understanding of modern data architecture, lakehouse patterns, Spark/PySpark, SQL, streaming, data quality, lineage

and governance.

l Working knowledge of GenAI and agentic patterns for manufacturing and supply chain knowledge assistance,

root-cause analysis, operational decision support and workflow automation.

l Ability to facilitate customer workshops, shape solution architectures, build business cases and communicate with

operations, supply chain, engineering, data and executive stakeholders.

l Experience leading distributed onsite-offshore teams and taking AI/ML initiatives from PoC through pilot to production.

Generic Managerial Skills

l Ability to lead a specialized AI/ML capability across accounts and teams without relying solely on formal authority.

l Strong consultative communication with plant, operations, supply chain, engineering, technology and executive

stakeholders.

l Ability to translate business and operational challenges into scalable analytics and AI solutions with clear value

measures.

l Experience coordinating distributed onsite-offshore teams, mentoring technical talent and governing delivery quality.

l Self-directed, pragmatic and comfortable building a new capability in an evolving unit; willing to travel to customer

locations as required

Salary Range: $160,700 - $220,000

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